# 计算train数据集的最大值,最小值,平均值
maximums, minimums, avgs = training_data.max(axis=0),
                                 training_data.max(axis=0),
                                 training_data.sum(axis=0)/training_data.shape[0] 
# 对数据进行归一化处理
for i in range(feature_num): 
   #print(maximums[i], minimums[i], avgs[i]) 
   data[:, i]=(data[:, i]-minimums[i]) / (maximums[i] -minimums[i])
